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- MakaleYalnız künye2019Detecting interaction/complexity within crowd movements using braid entropy
Akpulat, Murat; Ekinci, Murat
The segmentation of moving and non-moving regions in an image within the field of crowd analysis is a crucial process in terms of understanding crowd behavior. In many studies, similar movements were segmented according to the location, adjacency to each other, direction, and average speed. However, these segments may not in turn indicate the same types of behavior in each region. The purpose of this study is to better understand crowd behavior by locally measuring the degree of interaction/complexity within the segment. For this purpose, the flow of motion in the image is primarily represented as a series of trajectories. The image is divided into hexagonal cells and the finite time braid entropy (FTBE) values are calculated according to the different projection angles of each cell. These values depend on the complexity of the spiral structure that the trajectories generated throughout the movement and show the degree of interaction among pedestrians. In this study, behaviors of different complexities determined in segments are pictured as similar movements on the whole. This study has been tested on 49 different video sequences from the UCF and CUHK databases.
- BildiriYalnız künye2018Determining Complexity within the Crowd Movements
Akpulat, Murat; Ekinci, Murat
The segmentation of the moving and non-moving parts in an image within the crowd analysis studies is a crucial result in terms of understanding the behaviour. However, in many studies carried out, moving areas are assessed as making a set of movement that are similar in terms of location and of acceleration. In this study, what kind of interaction there exists among the people in a high-density crowd movement was studied. Initially, the motion data is represented as trajectories by using the optical flow and particle advection methods. The image is divided into equal hexagons and each area's topological entropy value is determined through Finite Time Braid Entropy (FTBE). This value depends on the complexity of the spiral structure that the trajectories generate throughout the movement and this value shows how much effective it is in the area. Eventually, through the complexity map that was generated, the behaviour of the crowd could be better understood and assessed. Also, in this way, possible abnormal conditions in the area can be predicted by monitoring each region and by setting off from the changes in the values of Braid entropy in time. The method was tested using the high-density crowd movements in the UCF database and results were presented.
- BildiriYalnız künye2017Observing the Entropy of Crowd Movements
Akpulat, Murat; Ekinci, Murat
Providing security and managing it as well as trying to understand how it behaves have become an important research topic in our day. The aim of this study is to calculate the entropy value of the crowd movement regionally and to track how it. changes in time. Because, excessive changes in the entropy value in time might point to abnormal behaviour in the region. The motion information obtained from the optical flow method from the image in parallel to the target was converted to motion orbits by particle advection. Motion orbits are mapped into by the Braid Theory and entropy value is calculated. Braid Theory is a mathematical method that is used to express entropy as a qualitative value by determining the interaction among the movement orbits. The results are tested according to the video sequence in the PETS2009 and UCF database and they show that this method is functional for observing how the entropy changes in time within the crowd movement.